Application of system dynamics and participatory spatial group model building in animal health: A case study of East Coast Fever interventions in Lundazi and Monze districts of Zambia Chisoni Mumba Presentation made at the Zambia Science Conference 2017-Reseachers Symposium, 22-24 th November 2017, AVANI, Livingstone, Zambia Theme: The role of Human Behaviour and environmental contextual issues in developing successful disease control Interventions in Livestock systems
Overview Initial focus: describe practices of traditional beef farmers in their production & marketing of cattle in Zambia Started as a big survey (n=770) to identify problem ECF most economically important production disease Despite the disease control efforts by stakeholders, ECF cases are increasing Research Question: Why does ECF oscillate over time? Can alternative approaches such as systems thinking contribute solutions to the complex ECF problem? To answer these research questions and inform the design & implementation of ECF interventions, We qualitatively investigated the influence of dynamic socioeconomic, cultural, and ecological contextual issues
Overview (2) Need for tools to assess these issues (research gap) Role of system dynamics (SD): a computer aided approach to policy analysis and design Interdisciplinary in nature & applies to dynamic problems arising in complex social, managerial, economic or ecological systems SD models can be developed through literature review, interviews and meetings Group model building (GMB) - use of communities/stakeholders in model conceptualization, formulation, analysis, & decision making SGMB - a new modification of a standard GMB highlighting spatial context of system
Overview (3) SGMB sessions applied facilitation tool called LayerStack developed at Lincoln University in NZ Used plastic acetates where each acetate denotes a data layer similar to a computer-based GIS. Helps stakeholders visualize many of the spatial factors of a particular research problem Eases facilitation process LayerStack enables SGMB to be done in any environment (e.g. outside, under a tree, etc.) Does not require use of computers, projectors, flip charts, or whiteboards like ordinary GMB processes Useful for developing countries
Methodology-Theories driving SD Grounded on 2 theories; personal construct & nonlinear dynamics (Sterman, 2000; Vennix, 1996) PC theory is a cognitive theory that defines every man as a scientist, who collects data to understand the world and creates mental models to predict the problem and control it (Kelly 1955) This is based on the fact that every man thinks & Thinking is the construction of mental models and simulating them in order to draw conclusions and make decisions (Richmond 2013) Mental models are images that we carry in our minds to simplify a representation of complex systems (Ford, 2010)
Theory of Nonlinear dynamics Spencer-wood, (2013) defines a dynamical nonlinear systems theory as, A paradigm in science that permits more accurate description and explanation of the evolution of most natural and cultural systems, patterns, and processes. This is because most systems are nonlinear to some extent
Why SGMB Since every man thinks (creates mental models), The use of SGMB makes SD mental models extremely close to reality as compared to desktop models (black box modelling) developed through literature review (Sterman, 2000) Improves quality of information received from stakeholders & Also grounds it spatially, providing more targeted details on the where of problems Allows bottom-up process of policy formulation & prioritization that take local needs into account Creates awareness, motivation, & platform for joint learning of solutions to common problems
Procedure of SGMB Script 1: Planning Script 2: Scene preparation Script 3: Introduction (hopes & fears) Script 4: Language of SD (concept models) Script 5: SGMB (facilitation tool) -Settlements, -Value chain actors & supporters, -Cattle production, -Cattle sales, -Disease -Household socioeconomic status Script 6: Problem identification (CLD, feedbacks) Script 7: Model development & simulation)
Pictorial description of SGMB
Digitised LayerStack
Learning outcomes from the SGMB process SGMB process revealed considerable diversity in the dynamic context of ECF due to differences in spatial patterns ECF interventions in Lundazi hindered by competition for land-use between crops & cattle Use of dip tanks obsolete, yet they are critical in keeping the host, vector and pathogen stable In Monze district, the model structure influenced by effects of climate change Climate change led to droughts & fewer floods that would otherwise provide an enabling environment for ticks & ECF parasite to thrive
Learning outcomes from the SGMB process The contrasts in access to cattle markets between the districts also influence ECF disease dynamics. E.g, in Monze district market is more internal while in Lundazi more externally-focused. External influence complicate effective ECF control interventions Variations in cultural shocks also influence ECF system behaviour Stigma associated with mixing of animals for cattle farmers of different social classes Effects stigma on dipping imply ECF is not only biologically determined but also socially constructed and maintained
Learning outcomes from the SGMB process Variations in agro-ecological zones & cattle herding practices also influence ECF system behaviour. Monze district practices transhumance cattle herding system in human-wildlife-livestock interface areas. The contact between cattle and wildlife in this system further complicates ECF disease control efforts
CLDs and Feedbacks
Modelling Process
Conclusions and Recommendations The spatial aspects and interactions of socio-economical, cultural, and ecological contextual issues play a critical role in designing and implementing effective and sustainable community-led ECF control policies These issues vary considerably across space and context, suggesting that a one-size-fits-all policy will not be effective The nature of disease and disease processes are just one part of the broader livestock system that includes market, socio-economic, and environmental factors. Household decisions made on the basis of social obligations, conventions, ethnic rivalry, or other household needs further thwart the technical, top-down efforts of policymakers to control disease
Conclusions and Recommendations These structures, and their interactions produce different patterns of disease endemicity over time, and which can be influenced by the introduction of public policies aimed at mitigating disease incidence From a policy perspective, SD models provide decision makers with insights on how interrelated factors /drivers influence disease patterns These insights are typically missing among decision-makers, We argue that a greater appreciation could help them develop policies that more effectively integrate technical solutions with socio-ecological interventions (e.g. farmer awareness, education, or specific socio-economic policies).
Policy leavers Internalising cattle sales through a creation of stable and sustainable markets Strategic immunisation and placement of dip tanks & establishing of veterinary infrastructure in cattle producing areas would help to change ECF system behaviour. Remedying social conflicts Involving stakeholders in policy design could improve the uptake of interventions Human development (population growth, urbanisation, agriculture) is a threat to biodiversity conservations. How do we deal with this?
Thank You